Seqanswers Leaderboard Ad

Collapse

Announcement

Collapse
No announcement yet.
X
 
  • Filter
  • Time
  • Show
Clear All
new posts

  • Unclear exon-exon connection after RSubjunc() usage

    Hi there.

    I posted this already somewhere else but didn't get any reply. (https://support.bioconductor.org/p/9156811/)

    "
    on my way to address alternatively used exons in a bulkRNAseq dataset I used fastq files and aligned reads with Rsubjunc (see in code below).

    To get a first impression I fed in the bam files of our control into IGV and looked a gene I know from from earlier studies and was surprised to see that the end of the transcript is split, as if the C-terminus was not connected on mRNA level. This confused be because the mRNA should be connected. Is there something, a setting, or something else I am missing here?

    I merged all six bam files in hope the merged file get more read connecting Ex45 with Ex46 (Total exon count is 48).

    Additionally, quiet a few reads are also found in the intronic regions, although not connected enough to say this is intron retention?

    I am happy to hear your opinion on this.

    Code:
    fastq_files <- list.files("../fastq/raw/", full.names = T, include.dirs = F)
    fastq_files_abs <- normalizePath(fastq_files)
    
    subjunc(index = "/home/chuddy/bioinformatics/ref_genomes/mouse_38/genome/subread/GRCm38",
    nthreads = 20,
    readfile1 = fastq_files_abs,
    sortReadsByCoordinates = TRUE)
    
    
    > sessionInfo( )
    R version 4.3.2 (2023-10-31)
    Platform: x86_64-pc-linux-gnu (64-bit)
    Running under: Ubuntu 20.04.6 LTS
    
    Matrix products: default
    BLAS: /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.9.0
    LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.9.0
    
    locale:
    [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C LC_TIME=de_CH.UTF-8 LC_COLLATE=en_US.UTF-8
    [5] LC_MONETARY=de_CH.UTF-8 LC_MESSAGES=en_US.UTF-8 LC_PAPER=de_CH.UTF-8 LC_NAME=C
    [9] LC_ADDRESS=C LC_TELEPHONE=C LC_MEASUREMENT=de_CH.UTF-8 LC_IDENTIFICATION=C
    
    time zone: Europe/Zurich
    tzcode source: system (glibc)
    
    attached base packages:
    [1] grid stats graphics grDevices utils datasets methods base
    
    other attached packages:
    [1] gridExtra_2.3 Rsubread_2.14.2 lubridate_1.9.3 forcats_1.0.0 stringr_1.5.1 dplyr_1.1.4 purrr_1.0.2
    [8] readr_2.1.5 tidyr_1.3.1 tibble_3.2.1 ggplot2_3.4.4 tidyverse_2.0.0
    
    loaded via a namespace (and not attached):
    [1] Matrix_1.6-5 gtable_0.3.4 compiler_4.3.2 tidyselect_1.2.0 scales_1.3.0 lattice_0.22-5
    [7] R6_2.5.1 generics_0.1.3 knitr_1.45 munsell_0.5.0 pillar_1.9.0 tzdb_0.4.0
    [13] rlang_1.1.3 utf8_1.2.4 stringi_1.8.3 xfun_0.41 timechange_0.3.0 cli_3.6.2
    [19] withr_3.0.0 magrittr_2.0.3 rstudioapi_0.15.0 hms_1.1.3 lifecycle_1.0.4 vctrs_0.6.5
    [25] glue_1.7.0 fansi_1.0.6 colorspace_2.1-0 tools_4.3.2 pkgconfig_2.0.3
    ​
    "

    Snippet below. I tried to use other bam files, where STAR was used and it worked and i used Rsubread with GTF annotation file support during mapping and there is also connects the exons.
    I wonder why such a good exon-exon connection is missed by Rsubread when no GTF file is used to help with mapping?
    ​​

Latest Articles

Collapse

  • seqadmin
    Genetic Variation in Immunogenetics and Antibody Diversity
    by seqadmin



    The field of immunogenetics explores how genetic variations influence immune responses and susceptibility to disease. In a recent SEQanswers webinar, Oscar Rodriguez, Ph.D., Postdoctoral Researcher at the University of Louisville, and Ruben Martínez Barricarte, Ph.D., Assistant Professor of Medicine at Vanderbilt University, shared recent advancements in immunogenetics. This article discusses their research on genetic variation in antibody loci, antibody production processes,...
    11-06-2024, 07:24 PM
  • seqadmin
    Choosing Between NGS and qPCR
    by seqadmin



    Next-generation sequencing (NGS) and quantitative polymerase chain reaction (qPCR) are essential techniques for investigating the genome, transcriptome, and epigenome. In many cases, choosing the appropriate technique is straightforward, but in others, it can be more challenging to determine the most effective option. A simple distinction is that smaller, more focused projects are typically better suited for qPCR, while larger, more complex datasets benefit from NGS. However,...
    10-18-2024, 07:11 AM

ad_right_rmr

Collapse

News

Collapse

Topics Statistics Last Post
Started by seqadmin, 11-08-2024, 11:09 AM
0 responses
208 views
0 likes
Last Post seqadmin  
Started by seqadmin, 11-08-2024, 06:13 AM
0 responses
152 views
0 likes
Last Post seqadmin  
Started by seqadmin, 11-01-2024, 06:09 AM
0 responses
80 views
0 likes
Last Post seqadmin  
Started by seqadmin, 10-30-2024, 05:31 AM
0 responses
26 views
0 likes
Last Post seqadmin  
Working...
X